CN117159916A

CN117159916A - Control method and device for ventricular assist device

Info

Publication number: CN117159916A
Application number: CN202310956222.XA
Authority: CN
Inventors: 戴明; 殷安云; 解启莲; 王新宇; 程洁; 杨浩; 李修宝; 余洪龙
Original assignee: Anhui Tongling Bionic Technology Co Ltd
Current assignee: Anhui Tongling Bionic Technology Co Ltd
Priority date: 2023-08-01
Filing date: 2023-08-01
Publication date: 2023-12-05

Abstract

The embodiment of the application provides a control method and a device for ventricular assist equipment, which relate to the technical field of medical equipment, and the method comprises the following steps: determining a mathematical model of the coupling of the target ventricular assist device and the sample heart environment as a simulated coupling model; determining a target model characterizing a mapping path between a heart pressure variation value and control parameters of a target ventricular assist device based on the simulated coupling model; obtaining a current actual heart pressure change value of a target heart environment, and determining a target control parameter of the target ventricular assist device based on the target model and the actual heart pressure change value; and controlling the target ventricular assist device according to the target control parameter so that the target ventricular assist device maintains a constant change in cardiac pressure of the target cardiac environment. By applying the scheme provided by the embodiment, the accurate control of the ventricular assist device can be realized.

Description

Control method and device for ventricular assist device

Technical Field

The application relates to the technical field of medical equipment, in particular to a control method and device of ventricular assist equipment.

Background

Ventricular assist devices are devices that provide support or assist functions for patients suffering from heart related diseases, such as heart failure, to assist the heart in pumping blood to other parts of the body.

Control of ventricular assist devices is a major problem. The control is reasonable, so that the ventricular unloading is facilitated, and the cardiac output, the pulse pressure difference and the blood flow pulsatility are satisfied; abnormal conditions such as aspiration, thrombosis, hemolysis, etc. may occur when the control is improper. Thus, there is a need for a control scheme for ventricular assist devices.

Disclosure of Invention

The embodiment of the application aims to provide a control method and a device for ventricular assist equipment, so as to accurately control the ventricular assist equipment. The specific technical scheme is as follows:

in a first aspect, an embodiment of the present application provides a method for controlling a ventricular assist device, where the method includes:

determining a mathematical model of the coupling of the target ventricular assist device and the sample heart environment as a simulated coupling model;

determining a target model characterizing a mapping path between a heart pressure variation value and control parameters of a target ventricular assist device based on the simulated coupling model;

obtaining a current actual heart pressure change value of a target heart environment, and determining a target control parameter of the target ventricular assist device based on the target model and the actual heart pressure change value;

And controlling the target ventricular assist device according to the target control parameter so that the target ventricular assist device maintains a constant change in heart pressure of the target heart environment.

In one embodiment of the present application, determining a target model characterizing a mapping path between a cardiac pressure variation value and a control parameter of a target ventricular assist device based on the simulated coupling model includes:

based on the simulation coupling model, determining a plurality of first sample heart pressure change values, determining first sample control parameters corresponding to each first sample heart pressure change value, and inputting each first sample heart pressure change value and the corresponding first sample control parameters into the simulation coupling model to obtain second sample heart pressure change values in adjacent unit time after unit time corresponding to each first sample heart pressure change value;

iteratively adjusting a weight coefficient of an initial model by adopting a plurality of target training samples, wherein each target training sample comprises a first sample heart pressure change value, a corresponding first sample control parameter and a corresponding second sample heart pressure change value, and the initial model is used for representing an initial mapping path between the heart pressure change value and the control parameter of target ventricular assist equipment;

And determining the initial model after the weight coefficient is adjusted as a target model.

In one embodiment of the present application, the iteratively adjusting the weight coefficient of the initial model by using the target training sample includes:

clustering target training samples to obtain a plurality of sample sets;

predicting an actual fitness of the first sample control parameter based on the first sample heart pressure change value, the first sample control parameter and the initial model in each target training sample contained in the current sample set, wherein the actual fitness characterizes the degree of control effect of the first sample control parameter as a target ventricular assist device under the condition that the first sample heart pressure change value reflects heart pressure change;

calculating the expected adaptation degree of the first sample control parameter based on the heart pressure change value of the second sample and the first sample control parameter contained in the current training sample;

and adjusting a weight coefficient of the initial model based on the difference between the actual adaptation degree and the expected adaptation degree, updating a current sample set under the condition that a convergence condition is not met, and returning to execute the step of predicting the actual adaptation degree of the first sample control parameter based on the first sample heart pressure change value, the first sample control parameter and the initial model in each target training sample contained in the current sample set based on the updated sample set until the convergence condition is met.

In one embodiment of the present application, the determining a plurality of first sample cardiac pressure variation values based on the simulated coupling model, and determining a first sample control parameter corresponding to each first sample cardiac pressure variation value includes:

determining a plurality of heart pressure variation values as first sample heart pressure variation values based on the simulated coupling model;

determining a control parameter corresponding to the first sample heart pressure change value based on a simulated coupling model;

a first sample control parameter is determined based on the control parameter threshold, the random control parameter, and the determined control parameter.

In one embodiment of the present application, the determining a plurality of first sample cardiac pressure variation values based on the simulated coupling model includes:

determining a value of each first sample heart pressure variation according to the following expression：

；

Wherein,for the average value of the estimated heart pressure variation values, +.>For the mean value of the actually measured heart pressure change values, i is the current parameter value in the simulated coupling model,/-, is>Indicating the current change rate>For the rotation speed parameter value in the simulation coupling model, a, b and c are all preset coefficients.

In one embodiment of the present application, the actual heart pressure variation value characterizes a pressure difference between an aorta and a left ventricle, and the controlling the target ventricular assist device according to the target control parameter so that the target ventricular assist device maintains a constant heart pressure variation of the target heart environment includes:

Predicting the starting time of the full support state of the target heart environment based on the current heart pressure of the target heart environment;

and controlling the target ventricular assist device according to the target control parameter at the starting moment of the predicted full support state so that the target ventricular assist device maintains the constant pressure difference between the aorta and the left ventricle in the target heart environment in the full support state.

In a second aspect, an embodiment of the present application provides a control apparatus for a ventricular assist device, the apparatus including:

the first model determining module is used for determining a mathematical model of the coupling of the target ventricular assist device and the sample heart environment as a simulation coupling model;

a second model determination module for determining a target model characterizing a mapping path between a heart pressure variation value and control parameters of a target ventricular assist device based on the simulated coupling model;

the control parameter determining module is used for obtaining the current actual heart pressure change value of the target heart environment and determining the target control parameter of the target ventricular assist device based on the target model and the actual heart pressure change value;

and the device control module is used for controlling the target ventricular assist device according to the target control parameter so that the target ventricular assist device maintains the constant change of the heart pressure of the target heart environment.

In one embodiment of the present application, the second model determining module includes:

the sample determining submodule is used for determining a plurality of first sample heart pressure change values based on the simulation coupling model, determining first sample control parameters corresponding to each first sample heart pressure change value, inputting each first sample heart pressure change value and the corresponding first sample control parameters into the simulation coupling model, and obtaining second sample heart pressure change values in adjacent unit time after unit time corresponding to each first sample heart pressure change value;

the model training sub-module is used for iteratively adjusting the weight coefficient of an initial model by adopting a plurality of target training samples, wherein each target training sample comprises a first sample heart pressure change value, a corresponding first sample control parameter and a corresponding second sample heart pressure change value, and the initial model is used for representing an initial mapping path between the heart pressure change value and the control parameter of the target ventricular assist device;

the model determination submodule is used for determining the initial model after the weight coefficient is adjusted as a target model.

In one embodiment of the present application, the model training submodule is specifically configured to cluster target training samples to obtain a plurality of sample sets; predicting an actual fitness of the first sample control parameter based on the first sample heart pressure change value, the first sample control parameter and the initial model in each target training sample contained in the current sample set, wherein the actual fitness characterizes the degree of control effect of the first sample control parameter as a target ventricular assist device under the condition that the first sample heart pressure change value reflects heart pressure change; calculating the expected adaptation degree of the first sample control parameter based on the heart pressure change value of the second sample and the first sample control parameter contained in the current training sample; and adjusting a weight coefficient of the initial model based on the difference between the actual adaptation degree and the expected adaptation degree, updating a current sample set under the condition that a convergence condition is not met, and returning to execute the step of predicting the actual adaptation degree of the first sample control parameter based on the first sample heart pressure change value, the first sample control parameter and the initial model in each target training sample contained in the current sample set based on the updated sample set until the convergence condition is met.

In one embodiment of the present application, the sample determining submodule is specifically configured to determine a plurality of cardiac pressure change values based on a simulated coupling model, as the first sample cardiac pressure change value; determining a control parameter corresponding to the first sample heart pressure change value based on a simulated coupling model; a first sample control parameter is determined based on the control parameter threshold, the random control parameter, and the determined control parameter.

In one embodiment of the present application, the sample determination submodule is specifically configured to determine each first sample cardiac pressure variation value according to the following expression：

；

In one embodiment of the present application, the actual heart pressure change value characterizes a pressure difference between an aorta and a left ventricle, and the device control module is specifically configured to predict a starting time of a full support state of the target heart environment based on a current heart pressure of the target heart environment; and controlling the target ventricular assist device according to the target control parameter at the starting moment of the predicted full support state so that the target ventricular assist device maintains the constant pressure difference between the aorta and the left ventricle in the target heart environment in the full support state.

In a third aspect, an embodiment of the present application provides an electronic device, including a processor, a communication interface, a memory, and a communication bus, where the processor, the communication interface, and the memory complete communication with each other through the communication bus;

a memory for storing a computer program;

and a processor, configured to implement the method steps described in the first aspect when executing the program stored in the memory.

In a fourth aspect, embodiments of the present application provide a computer-readable storage medium having stored therein a computer program which, when executed by a processor, implements the method steps of the first aspect described above.

From the above, it can be seen that, by applying the scheme provided by the embodiment of the present application, since the target control parameter is determined based on the real-time cardiac pressure variation value and the target model, on the one hand, the target model is based on the simulation coupling model in which the target ventricular assist device is coupled with the sample cardiac environment in the simulation environment, and the determined model is used for characterizing the mapping path between the cardiac pressure variation value and the control parameter, so that the accuracy of the target control parameter determined based on the target model is higher; on the other hand, since the real-time heart pressure change value reflects the real-time heart pressure change condition in the current heart environment, the target control parameter determined based on the real-time heart pressure change value can be adapted to the pressure change condition of the current heart environment. In summary, according to the above two aspects, according to the scheme provided by the embodiment, under the condition of adapting to the pressure change of the current heart environment, the ventricular assist device can be controlled according to relatively accurate control parameters, so as to maintain the heart pressure change constant, and realize accurate control.

Of course, it is not necessary for any one product or method of practicing the application to achieve all of the advantages set forth above at the same time.

Drawings

In order to more clearly illustrate the embodiments of the application or the technical solutions in the prior art, the drawings used in the embodiments or the description of the prior art will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the application, and other embodiments may be obtained according to these drawings to those skilled in the art.

Fig. 1 is a schematic structural diagram of an axial flow pump according to an embodiment of the present application;

fig. 2 is a flowchart of a control method of a first ventricular assist device according to an embodiment of the present application;

FIG. 3 is a flowchart illustrating a control method of a second ventricular assist device according to an embodiment of the present application;

fig. 4 is a flowchart of a control method of a third ventricular assist device according to an embodiment of the present application;

fig. 5 is a schematic structural diagram of a control device of a first ventricular assist device according to an embodiment of the present application;

FIG. 6 is a schematic structural diagram of a control device of a second ventricular assist device according to an embodiment of the present application;

Fig. 7 is a schematic structural diagram of an electronic device according to an embodiment of the present application.

Detailed Description

The following description of the embodiments of the present application will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present application, but not all embodiments. Based on the embodiments of the present application, all other embodiments obtained by the person skilled in the art based on the present application are included in the scope of protection of the present application.

The ventricular assist device of the present application may be attached to the apex of the left ventricle, the right ventricle, or both ventricles of the heart. The ventricular assist device may be an axial flow pump, a centrifugal pump, or a magnetic suspension pump.

The structure of the ventricular assist device will be described below with reference to fig. 1 by taking an axial flow pump as an example. Fig. 1 shows a schematic structural diagram of an axial flow pump, which comprises a pig tail pipe 106, a blood inflow port 105, a blood flow channel 104, a blood outflow port 103, a motor housing 102 and a catheter 101 which are sequentially connected and fixed, wherein a motor is installed in the motor housing 102, and a rotating shaft of the motor penetrates through the motor housing and is fixedly connected with an axial flow impeller in the blood flow channel 104.

The motor drives the axial flow impeller to rotate, and under this driving action, blood in the heart flows in from the blood inflow port 105, passes through the blood flow path 104, and flows out from the blood outflow port 103.

In the configuration shown in fig. 1, the motor is located within the heart when the ventricular assist device is placed in the patient. In addition to this structure, the motor can be connected to the impeller via a flexible drive shaft, so that when the ventricular assist device is placed in the patient, the motor is located outside the heart, thereby reducing the size of the ventricular assist device, and the motor drives the impeller to rotate via the flexible drive shaft, thereby achieving the auxiliary pumping function of the ventricular assist device.

The subject of execution of embodiments of the present application may be a controller of the ventricular assist device for detecting a parameter associated with the ventricular assist device/patient and controlling operation of the ventricular assist device.

Referring to fig. 2, fig. 2 is a flowchart of a control method of a first ventricular assist device according to an embodiment of the present application, where the method includes the following steps S201 to S204.

Step S201: a mathematical model of the coupling of the target ventricular assist device to the sample cardiac environment is determined as a simulated coupling model.

The target ventricular assist device refers to a ventricular assist device that is currently in need of control. The sample cardiac environment may be a cardiac environment for simulating a heart failure patient.

The simulation coupling model is used for simulating the coupling condition of the target ventricular assist device and the sample heart environment in a simulation environment. The simulation coupling model can be constructed in advance or in real time.

In constructing the simulated coupling model, in one embodiment, parameter values of each component included in the target ventricular assist device may be determined, and modeling is performed based on the determined parameters; parameter values for portions of the sample cardiac environment are determined and modeling is performed based on the determined parameters. And in the simulated digital environment, coupling the established digital model of the target ventricular assist device with the digital model of the sample heart environment, thereby obtaining a simulated coupling model.

Step S202: based on the simulated coupling model, a target model is determined that characterizes a mapping path between the heart pressure variation value and the control parameters of the target ventricular assist device.

The target model is used to characterize the mapping path between the heart pressure variation value and the control parameters of the target ventricular assist device. Wherein the heart pressure change value reflects the heart pressure change amplitude, and the heart pressure change value can be aortic pressure change, left ventricular pressure change, difference change between aortic pressure and left ventricular pressure, and the like; the control parameters may be the rotation speed, current, PWM (Pulse Width Modulation ) and other parameter values of the target ventricular assist device.

The target model may be a model based on a neural network model or a model based on a non-neural network model.

Because the target model is determined based on the simulation coupling model, the simulation coupling model reflects the coupling condition of the target ventricular assist device and the sample heart environment, and the mapping path between the heart pressure change value and the control parameter of the target ventricular assist device can be accurately determined based on the simulation coupling model, namely the target model can be accurately determined.

When determining the target model, in one embodiment, a plurality of heart pressure change value set values may be input into the simulation model, a plurality of control parameters are adopted to control the simulation model, and a control parameter with the optimal control effect is selected, so as to obtain a corresponding relation between the plurality of heart pressure change values and the control parameter, and the corresponding relation is fitted to obtain the target model.

Other embodiments of determining the object model may be found in the following examples corresponding to fig. 3, which are not described in detail herein.

Step S203: the method comprises the steps of obtaining a current actual heart pressure change value of a target heart environment, and determining target control parameters of target ventricular assist devices based on a target model and the actual heart pressure change value.

The target cardiac environment refers to the cardiac environment in which the target ventricular assist device is currently implanted. The actual heart pressure change value reflects the current heart pressure change amplitude of the target heart environment. The actual heart pressure change value may be a heart pressure change value in the current cardiac cycle or a heart pressure change value in a plurality of current cardiac cycles.

When the actual heart pressure change value is obtained, the heart pressure value of each current moment of the target heart environment can be obtained, and the difference between the maximum value and the minimum value is calculated and used as the actual heart pressure change value. The above-mentioned heart pressure values may be acquired using pressure sensor acquisitions inherited by ventricular assist devices.

When determining the control parameter, the actual heart pressure change value may be input into the target model, and the target model may determine, based on the mapping path, the control parameter corresponding to the actual heart pressure change value as the control parameter of the target ventricular assist device, since the target model characterizes the mapping path between the heart pressure change value and the control parameter.

Because the target model characterizes the mapping path between the heart pressure change value and the control parameters of the target ventricular assist device, the control parameters of the target ventricular assist device can be accurately determined by using the current actual heart pressure change value.

Step S204: the target ventricular assist device is controlled in accordance with the target control parameter such that the target ventricular assist device maintains a constant change in cardiac pressure of the target cardiac environment.

Because the target control parameter is determined based on the real-time heart pressure change value of the current target heart environment, the target control parameter is more suitable for the current real-time heart pressure environment, and when the target ventricular assist device is controlled according to the target control parameter, the target ventricular assist device can be better adapted to the current heart environment, so that the target ventricular assist device can be accurately controlled.

When the target ventricular assist device is controlled by using the target control parameter, the control target is to make the target ventricular assist device maintain the heart pressure change of the target heart environment constant. In controlling the above-mentioned target ventricular assist device, in one embodiment, the change data between the actual heart pressure change value and the preset heart pressure change value may be calculated, the control parameter corresponding to the change data is determined based on the target model, and the target control parameter of the target ventricular assist device is calculated based on the adjusted parameter of the control parameter of the target ventricular assist device and the control deviation, so that the heart pressure change value of the target ventricular assist device is always stabilized to the preset heart pressure change value, thereby realizing maintaining the heart pressure change of the target heart environment constant.

In one embodiment of the present invention, in the case that the actual cardiac pressure variation value represents the pressure difference between the aorta and the left ventricle, the starting time of the full support state of the current cardiac cycle of the target cardiac environment may be predicted based on the current cardiac pressure of the target cardiac environment; and controlling the target ventricular assist device according to the target control parameter at the beginning time of the predicted full support state so that the target ventricular assist device maintains the constant pressure difference between the aorta and the left ventricle in the target heart environment in the full support state.

The full support state characterizes the complete state of one cardiac cycle. The start time of the fully supported state may be the start time of the aortic systolic phase.

When predicting the starting time of the full support state, the first derivative and the multiple derivative of the current heart pressure of the target heart environment can be calculated, and the starting time of the full support state is determined based on the first derivative and the multiple derivative. For example, when the start time is the start time of the aortic systolic phase, the start time may be determined as the time when the first derivative reaches the second trough and the value of the multiple derivative is positive.

Since the target ventricular assist device is made to maintain the pressure difference between the aorta and the left ventricle constant in the target cardiac environment in the fully supported state, it is possible to improve the blood flow stability and the heart assist effect on the basis of providing fully supported blood flow support.

From the above, it can be seen that, by applying the scheme provided by the embodiment, since the target control parameter is determined based on the real-time heart pressure variation value and the target model, on one hand, the target model is based on a simulation coupling model for coupling the target ventricular assist device with the sample heart environment in the simulation environment, and the determined model for characterizing the mapping path between the heart pressure variation value and the control parameter, the accuracy of the target control parameter determined based on the target model is higher; on the other hand, since the real-time heart pressure change value reflects the real-time heart pressure change condition in the current heart environment, the target control parameter determined based on the real-time heart pressure change value can be adapted to the pressure change condition of the current heart environment. In summary, according to the above two aspects, according to the scheme provided by the embodiment, under the condition of adapting to the pressure change of the current heart environment, the ventricular assist device can be controlled according to relatively accurate control parameters, so as to maintain the heart pressure change constant, and realize accurate control.

In the aforementioned step S202 of the corresponding embodiment of fig. 2, steps S302-S304 of the corresponding embodiment of fig. 3 may be employed in addition to the determination of the object model in the mentioned manner. Based on this, fig. 3 is a flowchart of a control method of a second ventricular assist device according to an embodiment of the present application. The method includes the following steps S301-S306.

Step S301: a mathematical model of the coupling of the target ventricular assist device to the sample cardiac environment is determined as a simulated coupling model.

The step S301 is the same as the step S201 of the corresponding embodiment of fig. 2, and will not be described again.

Step S302: based on the simulation coupling model, determining a plurality of first sample heart pressure change values, determining first sample control parameters corresponding to each first sample heart pressure change value, inputting each first sample heart pressure change value and the corresponding first sample control parameters into the simulation coupling model, and obtaining second sample heart pressure change values in adjacent unit time after unit time corresponding to each first sample heart pressure change value.

In determining the first sample cardiac pressure variation value and the corresponding first sample control parameter, in one embodiment, a plurality of cardiac pressure variation values may be determined as the first sample cardiac pressure variation value in the coupling environment simulated by the simulated coupling model; then, a control parameter operated by the simulation coupling model in the case of the heart pressure variation value is determined as a sample control parameter, and the plurality of heart pressure variation values are determined as first sample heart pressure variation values.

In one embodiment of the present invention, each heart pressure variation value may be calculated according to the following expression:

；

And inputting the first sample heart pressure change value and the corresponding sample control parameter into the simulation coupling model to obtain a heart pressure change value of the next unit time output by the simulation coupling model, wherein the next unit time is the adjacent unit time after the unit time corresponding to the input first sample heart pressure change value.

In determining the first sample cardiac pressure variation value and the corresponding first sample control parameter, in another embodiment, a plurality of cardiac pressure variation values may be determined as the first sample cardiac pressure variation value based on the simulated coupling model; determining a control parameter corresponding to the first sample heart pressure change value based on the simulated coupling model; a first sample control parameter is determined based on the control parameter threshold, the random control parameter, and the determined control parameter.

The heart pressure variation value may be set in a simulation coupling model. Under the condition of setting the heart pressure change value, the control parameter operated by the simulation coupling model can be determined and used as the control parameter corresponding to the first sample heart pressure change value.

The control parameter threshold may include a minimum value and/or a maximum value of a control parameter, and the random control parameter is a randomly generated control parameter, and the random control parameter may be generated by using a preset noise data generation algorithm.

The random control parameters are introduced, so that the randomness degree of the selected control parameters is high, the divergence degree is good, and the adjustment effect can better reach the expected target when the weight coefficient is adjusted based on the selected control parameters later.

When determining the first sample control parameter, a sum of the random control parameter and the determined control parameter may be calculated, a control parameter range formed by the control parameter threshold and the calculated sum may be determined, the first sample control parameter may be selected from the control parameter ranges, one or more control parameters may be selected, and the control parameter of the preset sequence number in the control parameter range may be selected as the first sample control parameter.

Step S303: and adopting a plurality of target training samples to iteratively adjust the weight coefficient of the initial model.

Each target training sample comprises a first sample heart pressure change value, a corresponding first sample control parameter and a corresponding second sample heart pressure change value.

The initial model is used to characterize an initial mapping path between the heart pressure variation value and the control parameters of the target ventricular assist device. The initial mapping path reflected by the initial model has more noise data than the mapping path reflected by the target model. Thus, adjustments to the initial model are required.

When the weight coefficients are adjusted, each training sample can be iteratively input into the initial model according to the arrangement sequence of the target training samples. And after a preset number of target training samples are input, adjusting the weight coefficient of the initial model. Under the condition that the adjusted initial model does not meet the convergence condition, updating the current target training sample, and training by adopting the updated target training sample until the convergence condition is met. The convergence condition may be a preset adjustment number, a preset weight coefficient range, and the like. The adjustment may be referred to the following embodiment corresponding to fig. 4, and will not be described in detail here.

Step S304: and determining the initial model after the weight coefficient is adjusted as a target model.

Because the weight coefficient of the initial model is obtained by adopting a training sample through iterative adjustment, the initial model after the weight coefficient is adjusted, namely the target model, can accurately reflect the mapping path between the heart pressure change value and the control parameter.

Step S305: the method comprises the steps of obtaining a current actual heart pressure change value of a target heart environment, and determining target control parameters of target ventricular assist devices based on a target model and the actual heart pressure change value.

Step S306: the target ventricular assist device is controlled in accordance with the target control parameter such that the target ventricular assist device maintains a constant change in cardiac pressure of the target cardiac environment.

The steps S305-S306 are the same as the steps S203-S204 of the corresponding embodiment of fig. 2, and are not described herein.

From the above, since the target model is obtained by adopting the training sample to iteratively adjust the weight coefficient of the initial model, and since the training sample contains the heart pressure change and the control parameter in adjacent time, the initial model can learn the correlation characteristic between the heart pressure change and the control parameter during adjustment, so that the initial model after adjusting the weight coefficient, that is, the target model can more accurately reflect the mapping path between the heart pressure change and the control parameter, and further, the target ventricular assist device can be more accurately controlled.

In step S303 of the embodiment corresponding to fig. 3, when the weight coefficient of the initial model is adjusted, the method may be implemented according to steps S403 to S405 of the embodiment corresponding to fig. 4 described below. Based on this, fig. 4 is a flowchart of a control method of a third ventricular assist device according to an embodiment of the present application, where the method includes the following steps S401 to S408.

Step S401: a mathematical model of the coupling of the target ventricular assist device to the sample cardiac environment is determined as a simulated coupling model.

Step S402: based on the simulation coupling model, determining a plurality of first sample heart pressure change values, determining first sample control parameters corresponding to each first sample heart pressure change value, inputting each first sample heart pressure change value and the corresponding first sample control parameters into the simulation coupling model, and obtaining second sample heart pressure change values in adjacent unit time after unit time corresponding to each first sample heart pressure change value.

The steps S401 to S402 are the same as the steps S301 to S302 in the corresponding embodiment of fig. 3, and are not described herein.

Step S403: and clustering the target training samples to obtain a plurality of sample sets.

Each target training sample comprises a first sample heart pressure variation value, a corresponding first sample control parameter and a corresponding second sample heart pressure variation value.

In clustering, the clustering may be performed based on the first sample heart pressure variation value contained in the target training sample. Specifically, a pressure change difference threshold value may be preset, and a difference between the first sample heart pressure change values included in the plurality of target training samples satisfies the pressure change difference threshold value, as a target training sample included in one sample set. Thus, the number of sample sets is the same as the number of preset pressure change difference thresholds.

Of course, the clustering may also be performed based on other information, such as a unit time corresponding to the first sample heart pressure change value, the first sample control parameter, the second sample heart pressure change value, and so on. This is not limited thereto.

Step S404: the actual fitness of the first sample control parameter is predicted based on the first sample heart pressure variation value, the first sample control parameter, and the initial model in each target training sample contained in the current sample set.

The actual adaptation represents the extent to which the first sample control parameter acts as a control effect of the target ventricular assist device in the case of a change in heart pressure reflected by the first sample heart pressure change value.

The actual adaptation represents the extent to which the first sample control parameter acts as a control effect of the target ventricular assist device in the case of a change in heart pressure reflected by the first sample heart pressure change value. The higher the target fitness is, the better the control effect is, and the lower the target fitness is, the worse the control effect is.

In predicting the actual fitness, in one embodiment, an initial control parameter corresponding to the first sample cardiac pressure change value may be determined based on the initial model, a correlation between the initial control parameter and the first sample control parameter may be calculated, and the calculated correlation may be determined as the actual fitness.

In another embodiment, the actual fitness S may be calculated according to the following expression:

；

where N represents the total number of target training samples contained in the current sample set, i represents the sequence number of the target training samples contained in the current sample set,representing the first sample heart pressure variation value contained in the ith target training sample, +.>Representing the sample control parameters comprised by the ith target training sample,/->Function representing initial model +.>Representing a preset entropy prediction algorithm, +.>Representing preset coefficients, < >>Representing the attenuation factor.

Step S405: based on the second sample heart pressure variation value and the first sample control parameter contained in the current training sample, a desired fitness of the first sample control parameter is calculated.

The desired fitness characterizes the fitness achieved by the desired first sample control parameter. In one embodiment, the desired fitness T may be calculated according to the following expression:

；

Where N represents the total number of target training samples contained in the current sample set, i represents the sequence number of the target training samples contained in the current sample set,representing the first sample heart pressure variation value contained in the (i+1) th target training sample,/>Representing the sample control parameters comprised by the ith target training sample,/->Representing a preset parameter value calculation function, +.>Representing a preset entropy prediction algorithm, +.>Representing preset coefficients, < >>Representing the attenuation factor.

Step S406: and adjusting the weight coefficient of the initial model based on the difference between the actual adaptation degree and the expected adaptation degree, updating the current sample set under the condition that the convergence condition is not met, and returning to the execution step S404 based on the updated sample set until the convergence condition is met.

The difference between the actual fit and the desired fit reflects the deviation of the weight coefficients in the initial model. The larger the difference is, the larger the coefficient deviation is, and the smaller the difference is, the smaller the coefficient deviation is.

In adjusting the weight coefficient, in one embodiment, it may be determined whether a difference between the actual adaptation degree and the desired adaptation degree is greater than a preset threshold, if so, a loss value is calculated by using a preset loss function based on the difference, and the weight coefficient is adjusted according to a goal of minimizing the loss value. When the weight coefficient is adjusted, the weight coefficient can be adjusted according to a preset adjustment step length and an adjustment direction.

After the weight coefficient is adjusted, determining whether the initial model after current adjustment meets a convergence condition, and if so, ending training; if not, the current training sample is updated to train the initial model until the convergence condition is met.

Step S407: and determining the initial model after the weight coefficient is adjusted as a target model.

Step S408: the method comprises the steps of obtaining a current actual heart pressure change value of a target heart environment, and determining target control parameters of target ventricular assist devices based on a target model and the actual heart pressure change value.

Step S409: the target ventricular assist device is controlled in accordance with the target control parameter such that the target ventricular assist device maintains a constant change in cardiac pressure of the target cardiac environment.

The steps S407-S409 are the same as the steps S304-S306 of the corresponding embodiment of fig. 3, and are not described herein. From the above, it can be seen that, since the weight coefficients of the initial model are adjusted based on the difference between the actual adaptation degree and the desired adaptation degree of the first sample control parameter, the difference between the actual adaptation degree and the desired adaptation degree reflects the deviation condition of each weight coefficient in the initial model. Therefore, the weight coefficient can be accurately adjusted based on the above difference.

Corresponding to the control method of the ventricular assist device, the embodiment of the application also provides a control device of the ventricular assist device.

Referring to fig. 5, fig. 5 is a schematic structural diagram of a control device of a first ventricular assist device according to an embodiment of the present application, where the device includes:

a first model determination module 501 for determining a mathematical model of the coupling of the target ventricular assist device to the sample cardiac environment as a simulated coupling model;

a second model determination module 502 for determining a target model characterizing a mapping path between a heart pressure variation value and control parameters of a target ventricular assist device based on the simulated coupling model;

a control parameter determining module 503, configured to obtain a current actual heart pressure change value of a target heart environment, and determine a target control parameter of the target ventricular assist device based on the target model and the actual heart pressure change value;

a device control module 504 is configured to control the target ventricular assist device according to the target control parameter, so that the target ventricular assist device maintains a constant change in cardiac pressure of the target cardiac environment.

Referring to fig. 6, fig. 6 is a schematic structural diagram of a control device of a second ventricular assist device according to an embodiment of the present application, where the device includes:

a first model determining module 601, configured to determine a mathematical model of the coupling of the target ventricular assist device to the sample cardiac environment as a simulated coupling model;

the sample determining submodule 602 is configured to determine a plurality of first sample heart pressure change values based on the simulated coupling model, determine first sample control parameters corresponding to each first sample heart pressure change value, and input each first sample heart pressure change value and the corresponding first sample control parameter into the simulated coupling model to obtain second sample heart pressure change values in adjacent unit time after unit time corresponding to each first sample heart pressure change value;

the model training sub-module 603 is configured to iteratively adjust a weight coefficient of an initial model by using a plurality of target training samples, where each target training sample includes a first sample cardiac pressure variation value, a corresponding first sample control parameter, and a corresponding second sample cardiac pressure variation value, and the initial model is configured to characterize an initial mapping path between the cardiac pressure variation value and a control parameter of the target ventricular assist device;

The model determination submodule 604 is configured to determine an initial model after the weight coefficient is adjusted as a target model.

A control parameter determining module 605, configured to obtain a current actual heart pressure change value of a target heart environment, and determine a target control parameter of the target ventricular assist device based on the target model and the actual heart pressure change value;

a device control module 606 for controlling the target ventricular assist device in accordance with the target control parameter such that the target ventricular assist device maintains a constant change in cardiac pressure of the target cardiac environment.

In one embodiment of the present application, the model training submodule 603 is specifically configured to cluster target training samples to obtain a plurality of sample sets; predicting an actual fitness of the first sample control parameter based on the first sample heart pressure change value, the first sample control parameter and the initial model in each target training sample contained in the current sample set, wherein the actual fitness characterizes the degree of control effect of the first sample control parameter as a target ventricular assist device under the condition that the first sample heart pressure change value reflects heart pressure change; calculating the expected adaptation degree of the first sample control parameter based on the heart pressure change value of the second sample and the first sample control parameter contained in the current training sample; and adjusting a weight coefficient of the initial model based on the difference between the actual adaptation degree and the expected adaptation degree, updating a current sample set under the condition that a convergence condition is not met, and returning to execute the step of predicting the actual adaptation degree of the first sample control parameter based on the first sample heart pressure change value, the first sample control parameter and the initial model in each target training sample contained in the current sample set based on the updated sample set until the convergence condition is met.

From the above, it can be seen that, since the weight coefficients of the initial model are adjusted based on the difference between the actual adaptation degree and the desired adaptation degree of the first sample control parameter, the difference between the actual adaptation degree and the desired adaptation degree reflects the deviation condition of each weight coefficient in the initial model. Therefore, the weight coefficient can be accurately adjusted based on the above difference.

In one embodiment of the present application, the sample determining submodule 602 is specifically configured to determine a plurality of cardiac pressure change values as a first sample cardiac pressure change value based on a simulated coupling model; determining a control parameter corresponding to the first sample heart pressure change value based on a simulated coupling model; a first sample control parameter is determined based on the control parameter threshold, the random control parameter, and the determined control parameter.

In one embodiment of the present application, the sample determination submodule 602 is specifically configured to determine each of the cardiac pressure variation values according to the following expression ：

；

In one embodiment of the present invention, the actual heart pressure change value characterizes a pressure difference between the aorta and the left ventricle, and the device control module 606 is specifically configured to predict a starting time of the full support state of the target heart environment based on the current heart pressure of the target heart environment; and controlling the target ventricular assist device according to the target control parameter at the starting moment of the predicted full support state so that the target ventricular assist device maintains the constant pressure difference between the aorta and the left ventricle in the target heart environment in the full support state.

Corresponding to the control method of the ventricular assist device, the embodiment of the application also provides an electronic device.

Referring to fig. 7, fig. 7 is a schematic structural diagram of an electronic device according to an embodiment of the present application, including a processor 701, a communication interface 702, a memory 703 and a communication bus 704, where the processor 701, the communication interface 702, and the memory 703 communicate with each other through the communication bus 704,

a memory 703 for storing a computer program;

the processor 701 is configured to implement the method for controlling the ventricular assist device according to the embodiment of the present application when executing the program stored in the memory 703.

The communication bus mentioned above for the electronic devices may be a peripheral component interconnect standard (Peripheral Component Interconnect, PCI) bus or an extended industry standard architecture (Extended Industry Standard Architecture, EISA) bus, etc. The communication bus may be classified as an address bus, a data bus, a control bus, or the like. For ease of illustration, the figures are shown with only one bold line, but not with only one bus or one type of bus.

The communication interface is used for communication between the electronic device and other devices.

The Memory may include random access Memory (Random Access Memory, RAM) or may include Non-Volatile Memory (NVM), such as at least one disk Memory. Optionally, the memory may also be at least one memory device located remotely from the aforementioned processor.

The processor may be a general-purpose processor, including a central processing unit (Central Processing Unit, CPU), a network processor (Network Processor, NP), etc.; but also digital signal processors (Digital Signal Processor, DSP), application specific integrated circuits (Application Specific Integrated Circuit, ASIC), field programmable gate arrays (Field-Programmable Gate Array, FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components.

In still another embodiment of the present application, a computer readable storage medium is provided, where a computer program is stored, where the computer program is executed by a processor to implement a method for controlling a ventricular assist device provided by an embodiment of the present application.

In yet another embodiment of the present application, a computer program product containing instructions is also provided, which when run on a computer, cause the computer to perform the method for controlling a ventricular assist device provided by the embodiment of the present application.

In the above embodiments, it may be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented in software, may be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When loaded and executed on a computer, produces a flow or function in accordance with embodiments of the present application, in whole or in part. The computer may be a general purpose computer, a special purpose computer, a computer network, or other programmable apparatus. The computer instructions may be stored in or transmitted from one computer-readable storage medium to another, for example, by wired (e.g., coaxial cable, optical fiber, digital Subscriber Line (DSL)), or wireless (e.g., infrared, wireless, microwave, etc.). The computer readable storage medium may be any available medium that can be accessed by a computer or a data storage device such as a server, data center, etc. that contains an integration of one or more available media. The usable medium may be a magnetic medium (e.g., floppy Disk, hard Disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., solid State Disk (SSD)), etc.

It is noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.

In this specification, each embodiment is described in a related manner, and identical and similar parts of each embodiment are all referred to each other, and each embodiment mainly describes differences from other embodiments. In particular, for apparatus, electronic devices, computer readable storage medium embodiments, since they are substantially similar to method embodiments, the description is relatively simple, and relevant references are made to the partial description of method embodiments.

The foregoing description is only of the preferred embodiments of the present application and is not intended to limit the scope of the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application are included in the protection scope of the present application.

Claims

1. A method of controlling a ventricular assist device, the method comprising:

2. The method of claim 1, wherein the determining a target model characterizing a mapping path between cardiac pressure variation values and control parameters of a target ventricular assist device based on the simulated coupling model comprises:

3. The method of claim 2, wherein iteratively adjusting the weight coefficients of the initial model using a plurality of target training samples comprises:

clustering target training samples to obtain a plurality of sample sets;

4. A method according to claim 2 or 3, wherein determining a plurality of first sample heart pressure variation values based on the simulated coupling model and determining a first sample control parameter corresponding to each first sample heart pressure variation value comprises:

5. The method of claim 4, wherein determining a plurality of heart pressure variation values based on the simulated coupling model comprises:

determining each of the heart pressure variation values according to the following expression：

；

6. A method according to any of claims 1-3, wherein the actual heart pressure change value characterizes a pressure difference between an aorta and a left ventricle, the controlling the target ventricular assist device in accordance with the target control parameter such that the target ventricular assist device maintains a constant heart pressure change of the target heart environment, comprising:

7. A control device for a ventricular assist device, the device comprising:

8. The apparatus of claim 7, wherein the second model determination module comprises:

9. The apparatus of claim 8, wherein the model training submodule is specifically configured to cluster target training samples to obtain a plurality of sample sets; predicting an actual fitness of the first sample control parameter based on the first sample heart pressure change value, the first sample control parameter and the initial model in each target training sample contained in the current sample set, wherein the actual fitness characterizes the degree of control effect of the first sample control parameter as a target ventricular assist device under the condition that the first sample heart pressure change value reflects heart pressure change; calculating the expected adaptation degree of the first sample control parameter based on the heart pressure change value of the second sample and the first sample control parameter contained in the current training sample; and adjusting a weight coefficient of the initial model based on the difference between the actual adaptation degree and the expected adaptation degree, updating a current sample set under the condition that a convergence condition is not met, and returning to execute the step of predicting the actual adaptation degree of the first sample control parameter based on the first sample heart pressure change value, the first sample control parameter and the initial model in each target training sample contained in the current sample set based on the updated sample set until the convergence condition is met.

10. The apparatus according to claim 8 or 9, wherein the sample determination submodule is configured to determine a plurality of heart pressure change values as first sample heart pressure change values, in particular based on a simulated coupling model; determining a control parameter corresponding to the first sample heart pressure change value based on a simulated coupling model; a first sample control parameter is determined based on the control parameter threshold, the random control parameter, and the determined control parameter.

11. The apparatus according to claim 10, wherein the sample determination submodule is configured to determine each cardiac pressure change value according to the following expression：

；

12. The apparatus according to any one of claims 7-9, wherein the actual heart pressure variation value characterizes a pressure difference between an aorta and a left ventricle, the device control module being adapted in particular to predict a starting moment of a full support state of the target heart environment based on a current heart pressure of the target heart environment; and controlling the target ventricular assist device according to the target control parameter at the starting moment of the predicted full support state so that the target ventricular assist device maintains the constant pressure difference between the aorta and the left ventricle in the target heart environment in the full support state.